• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1625-1635
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• 1997

An extension of the weighted buddy system, called the extended-weighted buddy system, for dynamic memory allocation in an object-oriented computer is presented. The extended-weighted buddy system allows block sizes of $2^k,\;3*2^k,\;5*2^k,\;7*2^k$, whereas the original weighted buddy system allowed block sizes of $2^k\;and\;3*2^k$. This extension is achieved at only the cost of additional 3 bits per block for memory management unit. Simulation results are presented which compare our method with the weighted buddy system. These results indicate that, for uniform request distributions, our system has less internal memory fragmentation than the weighted buddy system(approximately 60%). And, for exponential request distributions, it has less internal memory fragmentation than the weighted buddy method (approximately 50%). The external fragmentation is greater for this system than the weighted buddy system. But, our system has less total memory fragmentation for exponential request distributions, and two systems take a similar total memory fragmentation for uniform request distributions, so we can substitutes the extended-weighted buddy system for weighted buddy system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.12-12
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• 2000

This paper consider a new weighted model reduction using block diagonal solutions of Lyapunov inequalities. With the input and/or output weighting function, the stability of reduced order system is quaranteed and a priori error bound is proposed. to achieve this, after finding the solutions of two Lyapunov inequalities and balancing the full order system, we find the reduced order systems using the direct truncation and the singular perturbation approximation. The proposed method is compared with other existing methods using numerical example.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.1
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• pp.1-12
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• 2019

This paper proposes a new motion vector smoothing and motion compensation method to increase the frame rate of videos. The proposed method reduces false motion vector smoothing by improving the weight with reflecting accuracy to overcome the limitation of the conventional motion vector smoothing using the adaptively weighted vector median. Also, to improve the interpolated image quality of the conventional OBMC(Overlapped Block Motion Compensation), a scheme that divides an original block into 4 sub-blocks and then generates the interpolated frame using the reestimated motion vector for each sub-block is proposed. The simulation results prove that the proposed method can provide much better objective and subjective image quality than the conventional method.

• Proceedings of the Acoustical Society of Korea Conference
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• 1985.10a
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• pp.87-94
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• 1985

In this paper, enhancement of speech corrupted by additive white or colored noise is stuided. The nuconstrained frequency-domain block least-mean-square (UFBLMS) adaptation algorithm and its frequency-weighted version are newly applied to speech enhancement. For enhancement of speech degraded by white noise, the performance of the UFBLMS algorithm is superior to the spectral subtraction method or Wiener filtering technique by more than 3 dB in segmented frequency-weighted signal-to-noise ratio(FWSNERSEG) when SNR of speech is in the range of 0 to 10 dB. As for enhancement of noisy speech corrupted by colored noise, the UFBLMS algorithm is superior to that of the spectral subtraction method by about 3 to 5 dB in FWSNRSEG. Also, it yields better performance by about 2 dB in FWSNR and FWSNRSEG than that of time-domain least-mean-square (TLMS) adaptive prediction filter(APF). In view of the computational complexity and performance improvement in speech quality and intelligibility, the frequency-weighted UFBLMS algorithm appears to yield the best performance among various algorithms in enhancing noisy speech corrupted by white or colored noise.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.366-370
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• 2003

This paper is on weighted model reduction using structurally balanced truncation. For a given weighted(single or double-sided) transfer function, a state space realization with the linear fractional transformation form is obtained. Then we prove that two block diagonal LMI(linear matrix inequality) solutions always exist, and it is possible to get a reduced order model with guaranteed stability and a priori error bound. Finally, two examples are used to show the validity of proposed weighted reduction method, and the method is compared with other existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.338-347
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• 2007

In this paper, a weighted block adaptive channel estimation (WBA-CE) for a space-time block-coded (STBC) single-carrier transmission with a cyclic-prefix is proposed. In operation of the WBA-CE, a STBC matrix-wise block for filter input symbols is first formulated. Applying a weighted a posteriori error vector-based least-square (LS) criterion for this block, the coefficient correction terms of the WBA-CE are then computed. An approximate steady-state excess mean-square error (EMSE) of the WBA-CE for the stationary optimal coefficient is also analyzed. Simulation results show in a time-varying typical urban (TU) channel that the proposed channel estimator provides better bit-error-rate (BER) performances than conventional algorithms such as the NLMS and RLS channel estimators.

• Journal of Broadcast Engineering
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• v.15 no.5
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• pp.672-680
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• 2010

This paper presents an adaptive quantization matrix selection scheme for H.264 video encoding. Conventional H.264 coding standard applies the same quantization matrix to the entire video sequence without considering local characteristics in each frame. In this paper, we propose block adaptive selection of quantization matrix according to edge directivity of each block. Firstly, edge directivity of each block is determined using intra prediction modes of its spatially adjacent blocks. If the block is decided as a directional block, new weighted quantization matrix is applied to the block. Otherwise, conventional quantization matrix is used for quantization of the non-directional block. Since the proposed weighted quantization is designed based on statistical distribution of transform coefficients in accordance with intra prediction modes, we can achieve high coding efficiency. Experimental results show that the proposed scheme can improve coding efficiency by about 2% in terms of BD bit-rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.730-736
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• 2009

It is more important to analysis of huge gemonics data in Bioinformatics. Here we present a novel datamining approach to predict structure and function using protein's primnary structure only. We propose not also to develope n-Block substring search algorithm in reducing enormous search space effectively in relation to feature selection, but to formulate weighted linear algorithm in a prediction of structure and function of a protein using primary structure. And we show efficient in protein domain characterization and classification by calculation weight value in determining domain association in each selected substring, and also reveal that more efficient results are acquired through claculated model score result in an inference about degree of association with each CDS(coding sequence) in domain.

• Journal of information and communication convergence engineering
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• v.1 no.3
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• pp.119-122
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• 2003

In this paper presents equations which describe an average weighted spectrum of errors and average block error probabilities for noncoherent frequency shift keying (NCFSK) used in D-branch maximal ratio combining (MRC) diversity in independent very slow nonselective Nakagami fading channels. The average is formed over the instantaneous receiver signal to noise ratio (SNR) after combining. the analysis is limited to additive Gaussian noise.

• Journal of the Korean Statistical Society
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• v.16 no.1
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• pp.21-25
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• 1987

The combined estimator of inter- and intra-block estimators in incomplete block designs can be expressed as a weighted average of two location estimators. The weight should be between 0 and 1. However, the negative variance component estimate could result in the weight being negative or larger than 1. In this paper, we show that if two location estimators have symmetric unimodal distributions, truncating the weight to 0 or 1 accordingly improves the combined estimator under an arbitrary convex loss function.